Computer Science is experimenting with new approaches to ubiquitous computing (UBICOMP), which includes adding intelligence not only in devices, but also to the environment. In the case of industrial automation, intelligence may be distributed in the network without delegating the intelligence to a server or to a human-machine interface.
As a specific example, imaging systems, such as 2D and 3D readers, are often connected in an industrial network as nodes on the network. In order to relieve processing constraints the main computing nodes and free more bandwidth on a network, available computing power in the network should be distributed. One current solution has been to place devices that routinely exchange high volumes of data close enough in the network so as to minimize cluttering communications across the entirety of the network.
In factory automation and shop floor fields, “energy management” is becoming a key topic due to new “green requirements” originally born in the building automation sector. Energy management can be thought as the proactive, organized, and systematic set up, monitoring, and measurement of energy consumption in order to meet some predefined requirement while taking into account environmental and economic objectives.
Concern over the global energy problem (availability and cost) as well as demands for greater environmental protection represent a challenge for devices that share resources in the near future. Distributed industrial auto-identification systems, such as vision systems, where a required power supply is not negligible and is strongly correlated to the performance of the system, present a unique problem.